Application of Polynomial Models in Bayesian Fusion of Humidity Sensors

Author:

Nikovski Plamen1,Doychinov Nikolay1

Affiliation:

1. University of Food Technologies, 26 Maritza Blvd., 4002, Plovdiv, Bulgaria

Abstract

Local polynomial trend models are a special class of state-space models that can be used without having the full information about the process under study, since most of their parameters are embodied in the state vector and estimated immediately. This makes them attractive for use in signal processing. The present work considers problems that arise when using a polynomial model with a local quadratic trend for Bayesian fusion of two humidity sensors. The unknown sensor biases make it impossible for the model to satisfy the observability conditions. There is currently no general solution to this problem. To overcome this difficulty, an approach is presented where the humidity measurement result implicitly includes the bias of one of the sensors. The results of the study can be used to fuse quantities other than humidity when two or more sensors are available.

Publisher

Association for Information Communication Technology Education and Science (UIKTEN)

Subject

Management of Technology and Innovation,Information Systems and Management,Strategy and Management,Education,Information Systems,Computer Science (miscellaneous)

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Mathematical Model for Increasing Accuracy when Measuring Linear Quantities in Conditions of External Mechanical Impacts;2023 XXXIII International Scientific Symposium Metrology and Metrology Assurance (MMA);2023-09-07

2. Increasing the Accuracy of Making Threaded Gauges Based on Statistical Methods;2023 XXXIII International Scientific Symposium Metrology and Metrology Assurance (MMA);2023-09-07

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